Uji Sensitivitas Metode Aras Dengan Pendekatan Metode Pembobotan Kriteria Sahnnon Entropy Dan Swara Pada Penyeleksian Calon Karyawan

Penelitian ini melakukan uji sensitivitas metode Additive Ratio Assessment (ARAS) pada penyeleksian calon karyawan dengan pendekatan pembobotan kriteria menggunakan metode Shannon Entropy dan metode Stepwise Weight Assessment Ratio Analysis (SWARA) yang bertujuan untuk mengukur seberapa sensitif metode ini jika diterapkan pada sebuah kasus pengambilan keputusan. Data yang digunakan ialah data penyeleksian calon karyawan. Uji Sentitivitas pada penelitian ini digunakan untuk mengetahui metode yang lebih sensitif saat diterapkan pada suatu kasus. Metode perangkingan menggunakan ARAS karena metode perangkingan ini memiliki fungsi utilitas dan nilai optimalisasi. Metode Shannon Entropy bobot kriteria diperoleh berdasarkan perhitungan data alternatif penyeleksian karyawan, sedangkan metode SWARA bobot kriteria diperoleh dari pakar atau si pengambil keputusan. Hasil penelitian ini menunjukkan bahwa metode yang paling sensitif dengan kasus penyeleksian calon karyawan adalah metode SWARA-ARAS yang pemberian bobotnya berdasarkan pakar atau si pengambil keputusan dengan hasil sebesar 91,24203% lebih tinggi dibandingkan metode Shannon Entropy-ARAS yang hasil sebesar 74,75263%

Penerapan Metode SWARA-ELECTRE Dalam Pemilihan Penerima Bantuan Sosial Kelompok Usaha Bersama (KUBE)

Kelompok Usaha Bersama (KUBE) merupakan bentuk bantuan sosial pemerintah untuk membantu masyarakat yang kurang mampu. Saat ini, proses seleksi calon penerima bantuan KUBE masih dilakukan secara manual, sehingga membutuhkan waktu yang lama dan rentan terhadap kesalahan atau kecurangan. Untuk mengatasi hal tersebut, penelitian ini mengembangkan sebuah sistem pendukung keputusan menggunakan metode Stepwise Weight Assessment Ratio Analysis dan Elimination ET Choix Traduisant LA Realite untuk membantu karyawan di bidang Penanganan Fakir Miskin Dinas Sosial Garut dalam melakukan seleksi calon penerima bantuan. Sistem ini memanfaatkan metode SWARA untuk menetapkan bobot kriteria pada pemilihan penerima bantuan KUBE dan metode ELECTRE untuk perangkingan alternatif. Metode SWARA mengevaluasi pentingnya tiap kriteria, sementara metode ELECTRE membandingkan alternatif berdasarkan kriteria yang sama. Gabungan kedua metode ini meningkatkan efisiensi dan ketepatan seleksi, mengurangi risiko kesalahan dan kecurangan yang mungkin terjadi dalam proses manual sebelumnya. Hasil penelitian menyimpulkan bahwa sistem ini berhasil memberikan rekomendasi alternatif penerima bantuan KUBE dengan perolehan poin sebanyak 3 yaitu Domba Sagara 2 yang berada pada peringkat pertama, Domba Sagara 1 pada peringkat kedua, dan Berkah Wijaya pada peringkat ketiga. Metode Stepwise Weight Assessment Ratio Analysis terbukti mampu menghitung bobot kriteria dengan akurat, sedangkan metode Elimination ET Choix Traduisant LA Realite efektif dalam melakukan perangkingan pada alternatif dengan baik. Selain itu, sistem ini juga mencapai tingkat akurasi sebesar 90% berdasarkan perhitungan menggunakan confusion matrix. Penelitian ini memberikan kontribusi penting dalam meningkatkan efisiensi dan keakuratan proses seleksi penerima bantuan sosial KUBE

OWA-Based Multi-Criteria Decision Making based on Fuzzy Methods

One of the most important challenges in Multi-Attribute Decision Making (MADM) problem is "How can the optimal weights of the criteria be determined properly by the decision maker?". In the relevant research literature, various methods based on the requirements and assumptions of the problem were introduced to determine the weights of the criteria. In this regard, in particular, the Yager's OWA operator is one of the most significant and widely used approaches to evaluate the weight of criteria. But there is a drawback, which is that the results of Yager's OWA operator depend only on the level and size of decision-maker's risk and the dimension of the criteria. Therefore, in this paper, using a multi-objective decision making approach, we try to express this MADM challenge in the form of a generalization of the Yager's OWA operators and Ahn's method. One of the advantages of this generalization is that the proposed method uses all the information in the decision matrix compared to the methods proposed by Yager's OWA operators and the Ahn's method. The proposed approach is also able to enter the types of preferences considered by the decision maker for the criteria calculations as crisp or fuzzy quantities. Numerical examples and real dataset analysis based on a survey of students' opinions on teaching activities are provided

An extended stepwise weight assessment ratio analysis (SWARA) method for improving criteria prioritization process

The process of criteria prioritization and weighting is an important part of multiple attributes decision making. The most frequently applied multi-attribute decision-making weighting tools include analytical hierarchy process, stepwise weight assessment ratio analysis, factor relationship, and best–worst method. When policies are at the core of decision making, stepwise weight assessment ratio analysis method is the most efficient method for criteria evaluation. It involves two important steps: the first is to prioritize the criteria by consulting experts, while the second is the weighting process. This research seeks to extend stepwise weight assessment ratio analysis to improve the quality of the decision-making process by incorporating the reliability evaluation of experts’ idea into the first step. Such a component is absent from the first step in all other similar models. Thus, an extended version of stepwise weight assessment ratio analysis can be applied for such evaluation. To test the applicability and performance of the proposed method, a numerical example from an earlier study was used. The proposed version can replace the classic version in future studies as an improved method in decision-making area.Sin financiaciónNo data JCR 20180.617 SJR (2018) Q2, 126/1355 Software, 36/84 Geometry and Topology, 42/164 Theoretical Computer ScienceNo data IDR 2018UE

Personalized Product Evaluation Based on GRA-TOPSIS and Kansei Engineering

With the improvement of human living standards, users’ requirements have changed from function to emotion. Helping users pick out the most suitable product based on their subjective requirements is of great importance for enterprises. This paper proposes a Kansei engineering-based grey relational analysis and techniques for order preference by similarity to ideal solution (KE-GAR-TOPSIS) method to make a subjective user personalized ranking of alternative products. The KE-GRA-TOPSIS method integrates five methods, including Kansei Engineering (KE), analytic hierarchy process (AHP), entropy, game theory, and grey relational analysis-TOPSIS (GRA-TOPSIS). First, an evaluation system is established by KE and AHP. Second, we define a matrix variate—Kansei decision matrix (KDM)—to describe the satisfaction of user requirements. Third, the AHP is used to obtain subjective weight. Next, the entropy method is employed to obtain objective weights by taking the KDM as input. Then the two types of weights are optimized using game theory to obtain the comprehensive weights. Finally, the GRA-TOPSIS method takes the comprehensive weights and the KMD as inputs to rank alternatives. A comparison of the KE-GRA-TOPSIS, KE-TOPSIS, KE-GRA, GRA-TOPSIS, and TOPSIS is conducted to illustrate the unique merits of the KE-GRA-TOPSIS method in Kansei evaluation. Finally, taking the electric drill as an example, we describe the process of the proposed method in detail, which achieves a symmetry between the objectivity of products and subjectivity of users

Investigation of empty container shortage based on SWARA-ARAS methods in the COVID-19 era

A shortage of empty containers has become a global crisis with more devastating effects than during previous periods when combined with various problems arising from the COVID-19, such as an increase in an imbalance of global trade between supply and demand, a decrease in the workforce, and restrictions by countries or regional quarantine practices. The absence of empty containers in regions where they are needed slows down industrial activities and locks the global supply networks, necessitating the use of alternative methods that are inefficient. Although this shortage causes many disruptions in global trade, solutions to the issue have not been studied in detail. Therefore, the aim of this study was to determine the issues caused by the shortage of empty containers and to rank the appropriate solutions. Four main criteria and sixteen subcategories used to define the issues, as well as a multi criteria decision model comprising five criteria for the solutions, were proposed based on information from the literature, sectorial publications, and expert opinions. The issues’ weighted order of importance in our proposed model was calculated using the SWARA (Step-wise Weight Assessment Ratio Analysis) method; solutions were ranked using the ARAS (Additive Ratio Assessment) method. The results of the study revealed that the issues were ranked in importance as cost increases, uncertainty in the supply chain, volume loss, and increases in blank sailing announcements. Appropriate solutions were ranked as booking guarantee applications and information communication technologies, using shipper-owned containers, inducement calls, and E2E (end to end) delivery services

Modeli za evaluaciju i izbor zaposlenih zasnovani na metodama višekriterijumskog odlučivanja

У данашње време савремене организације се налазе пред великим изазовом, а све због динамичнијих и захтевнијих услова пословања. Запослени представљају кључни фактор на основу којег организације постижу и задржавају конкурентску предност. Из тог разлога, менаџмент људских ресурса представља важну пословну активност од које зависи успех организације. Из тог разлога, процесу регрутације и селекције кадрова се посвећује посебна пажња. Избор компетентних запослених се најчешће одвија у кратком временском интервалу, док са друге стране организација тежи да запослени остану што дуже у организацији. Током времена предложено је више приступа, алата и техника за избор запослених. Традиционалне методе најчешће за евалуацију кандидата укључују статистичке анализе, тестове личности и сл. У циљу смањења субјективности и интуитивности у процесу селекције кадрова, на располагању су и технике које се заснивају на примени метода вишекритеријумског одлучивања. Сходно томе, докторска дисертација има за циљ да предложи вишекритеријумске оквире тј. моделе за избор кадрова. Модели се заснивају на примени Step‐Wise Weight Assessment Ratio Analysis - SWARA , Technique for Order of Preference by Similarity to Ideal Solution - TOPSIS и Combined Compromise Solution – CoCoSo метода. SWARA метода је у докторској дисертацији примењена за дефинисање тежина евалуационих критеријума. За коначно рангирање алтернатива односно кандидата примењене су TOPSIS и CoCoSo методе.U današnje vreme savremene organizacije se nalaze pred velikim izazovom, a sve zbog dinamičnijih i zahtevnijih uslova poslovanja. Zaposleni predstavljaju ključni faktor na osnovu kojeg organizacije postižu i zadržavaju konkurentsku prednost. Iz tog razloga, menadžment ljudskih resursa predstavlja važnu poslovnu aktivnost od koje zavisi uspeh organizacije. Iz tog razloga, procesu regrutacije i selekcije kadrova se posvećuje posebna pažnja. Izbor kompetentnih zaposlenih se najčešće odvija u kratkom vremenskom intervalu, dok sa druge strane organizacija teži da zaposleni ostanu što duže u organizaciji. Tokom vremena predloženo je više pristupa, alata i tehnika za izbor zaposlenih. Tradicionalne metode najčešće za evaluaciju kandidata uključuju statističke analize, testove ličnosti i sl. U cilju smanjenja subjektivnosti i intuitivnosti u procesu selekcije kadrova, na raspolaganju su i tehnike koje se zasnivaju na primeni metoda višekriterijumskog odlučivanja. Shodno tome, doktorska disertacija ima za cilj da predloži višekriterijumske okvire tj. modele za izbor kadrova. Modeli se zasnivaju na primeni Step‐Wise Weight Assessment Ratio Analysis - SWARA , Technique for Order of Preference by Similarity to Ideal Solution - TOPSIS i Combined Compromise Solution – CoCoSo metoda. SWARA metoda je u doktorskoj disertaciji primenjena za definisanje težina evaluacionih kriterijuma. Za konačno rangiranje alternativa odnosno kandidata primenjene su TOPSIS i CoCoSo metode